Version 1
: Received: 10 September 2021 / Approved: 13 September 2021 / Online: 13 September 2021 (11:54:04 CEST)
How to cite:
Bandyopadhyay, S.; Bhaumik, A.; Poddar, S. Skin Disease Detection: Machine Learning vs Deep Learning. Preprints2021, 2021090209. https://doi.org/10.20944/preprints202109.0209.v1
Bandyopadhyay, S.; Bhaumik, A.; Poddar, S. Skin Disease Detection: Machine Learning vs Deep Learning. Preprints 2021, 2021090209. https://doi.org/10.20944/preprints202109.0209.v1
Bandyopadhyay, S.; Bhaumik, A.; Poddar, S. Skin Disease Detection: Machine Learning vs Deep Learning. Preprints2021, 2021090209. https://doi.org/10.20944/preprints202109.0209.v1
APA Style
Bandyopadhyay, S., Bhaumik, A., & Poddar, S. (2021). Skin Disease Detection: Machine Learning vs Deep Learning. Preprints. https://doi.org/10.20944/preprints202109.0209.v1
Chicago/Turabian Style
Bandyopadhyay, S., Amiya Bhaumik and Sandeep Poddar. 2021 "Skin Disease Detection: Machine Learning vs Deep Learning" Preprints. https://doi.org/10.20944/preprints202109.0209.v1
Abstract
Skin disease is a very common disease for humans. In the medical industry detecting skin disease and recognizing its type is a very challenging task. Due to the complexity of human skin texture and the visual closeness effect of the diseases, sometimes it is really difficult to detect the exact type. Therefore, it is necessary to detect and recognize the skin disease at its very first observation. In today's era, artificial intelligence (AI) is rapidly growing in medical fields. Different machine learning (ML) and deep learning(DL) algorithms are used for diagnostic purposes. These methods drastically improve the diagnosis process and also speed up the process. In this paper, a brief comparison between the machine learning process and the deep learning process was discussed. In both processes, three different and popular algorithms are used. For the machine Learning process Bagged Tree Ensemble, K-Nearest Neighbor (KNN), and Support Vector Machine(SVM) algorithms were used. For the deep learning process three pre-trained deep neural network models
Keywords
Skin Disease Detection; Machine Learning (ML); Deep Learning(DL); Artificial Intelligence
Subject
Biology and Life Sciences, Plant Sciences
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
